Staff Data Engineer

Teamworks

Staff Data Engineer co-defining AWS lakehouse architecture and leading data maturity initiatives for innovative sports tech platform. Collaborating across teams to integrate performance data into analytics and ML insights.

Posted 6/10/2026full-timeRemote • North Carolina • 🇺🇸 United StatesLead💰 $216,000 per yearWebsite

Tech Stack

Tools & technologies

AWSCloudPythonSparkTerraform

About the role

Key responsibilities & impact

Define the technical architecture and platform standards for our lakehouse on AWS: distributed cloud architecture, schema conventions, multi-tenant isolation, and integration design
Lead design and delivery of the production pipelines that consolidate performance and product data, and own data modeling for complex entities (time-series, hierarchical, multi-source) so the models serve products, analytics, and ML
Introduce just enough data governance, ownership, and stewardship to raise our data maturity, and lay the catalog and semantic-layer foundation that analytics, ML, and AI agents can reason over
Author and maintain the Data Platform playbook (reusable patterns, ADRs, runbooks, Terraform modules) with data quality and reliability built in, so product teams can self-serve new datasets and integrations
Lead delivery end to end, from requirements and planning through coordinating workstreams and translating status to senior leadership and non-technical partners
Mentor engineers across levels, raise the bar through design review and on-call ownership, and be the engineering voice shaping the platform roadmap

Requirements

What you’ll need

10+ years of data engineering or related experience, with strong Python for pipelines, transformations, and platform tooling
Deep expertise designing, operating, and setting direction for lakehouse platforms (Delta Lake, Iceberg, or Hudi) and modern processing engines (Spark, Databricks, Trino, or Snowflake) at production scale, with the judgment to make the hard tradeoffs and troubleshoot them
Expert AWS and distributed cloud architecture experience (S3, IAM, Glue, EMR/Lambda, networking), fluent writing Terraform and the best practices for implementing those designs
Deep data modeling and schema design for complex entities (time-series, hierarchical, multi-source) in multi-tenant environments, across multiple systems you've built (warehouses, lakehouses, relational), plus proven integration standards across teams (event-driven, API, batch)
Track record of standing up or significantly maturing a data platform from ambiguous goals, including the organizational work of aligning leaders and teams and communicating decisions to senior and non-technical stakeholders through RFCs and ADRs
Familiarity with how data governance, ownership, and stewardship programs are introduced, and the judgment to apply just enough to raise data maturity without over-engineering it

Benefits

Comp & perks

Offers Equity
Offers Bonus

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Pythondata modelingschema designlakehouse platformsDelta LakeIcebergHudiSparkDatabricksTerraform

Soft Skills

leadershipmentoringcommunicationcollaborationproblem-solvingorganizational skillsstakeholder managementdesign reviewtechnical guidancestatus reporting